Self-driving technologies have demonstrated significant potential to transform human mobility. However, single-agent systems face inherent limitations in perception and decision-making capabilities. Transitioning from self-driving vehicles to cooperative multi-vehicle systems and large-scale intelligent transportation systems is essential to enable safer and more efficient mobility. Realizing such sophisticated mobility systems introduces significant challenges, requiring comprehensive tools and models, simulation environments, real-world datasets, and deployment frameworks. This tutorial will delve into key areas of driving automation, beginning with advanced end-to-end self-driving techniques such as vision-language-action (VLA) models, interactive prediction and planning, and scenario generation. The tutorial emphasizes V2X communication and cooperative perception in real-world settings, as well as datasets including V2X-Real and V2XPnP. It also covers simulation and deployment frameworks for urban mobility, such as MetaDrive, MetaUrban, and UrbanSim. By bridging foundational research with real-world deployment, this tutorial offers practical insights into developing future-ready autonomous mobility systems.